Image characteristic matching method based on improved shape contexts

An image feature and matching method technology, applied in the field of medical computer, can solve the problems of high dimension, prone to wrong matching, and reduced matching efficiency.

Active Publication Date: 2017-11-07
BEIJING INSTITUTE OF TECHNOLOGYGY +1
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AI Technical Summary

Problems solved by technology

[0005] In order to overcome the problems of existing image feature matching algorithms, such as similar local gray distributions in different regions of the image, prone to error matching

Method used

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  • Image characteristic matching method based on improved shape contexts
  • Image characteristic matching method based on improved shape contexts
  • Image characteristic matching method based on improved shape contexts

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Embodiment Construction

[0040] The specific implementation process of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0041] An image feature matching method based on improved shape context, its step flow chart is as follows figure 1 shown. Specifically include the following steps.

[0042] Step 1. Extract SIFT feature points from the first image to be matched and the second image to obtain a feature point set of the global image, and perform rough matching according to the SIFT algorithm.

[0043] Step 2. Classify the SIFT feature points of the above two images by clustering, and segment to obtain several subsets of the shape point set. Among them, the clustering method is preferably an AP (affinity propagation) clustering method. Specifically:

[0044] S2.1: Use the AP (affinity propagation) clustering method to divide the SIFT feature points on the first image into a certain number of regions, and the shape point set S of the first image...

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Abstract

The invention discloses an image characteristic matching method based on improved shape contexts, and belongs to the medical computer technology field. The image characteristic matching method comprises steps that required SIFT characteristic points are extracted from two to-be-matched images, and according to an SIFT algorithm, rough matching is carried out; the improved shape contexts of every matching point with respect to other points are calculated; whether similarity between the relative relation among the matching points of the first image and the relative relation among the matching points of the second image exists is observed, and then whether the characteristic matching of the two images is correct is determined. The improved method is advantageous in that under a precondition of not changing dimensions of characteristic descriptors, the improved shape contexts are used to eliminate wrong matching phenomena, and therefore matching precision is improved to a great extent, and at the same time, the method is resistant to noise influences and image geometric changes.

Description

technical field [0001] The invention relates to an image feature matching method, in particular to an image SIFT feature matching method based on improved shape context, and belongs to the technical field of medical computers. Background technique [0002] After the 20th century, medical image technology has changed rapidly. Medical images can be divided into two types according to the information they provide. One is anatomical structure images, such as CT, MRI, and B-ultrasound. Functional information and metabolic information of organs are powerless; the second is functional images, such as SPECT, PET, etc., which can completely display relevant information of organs, but the pixel resolution is relatively low, and some details of anatomy are powerless. Although these studies on medical images have been of great help, due to the limitations of providing image information, doctors need to combine their experience, spatial conception and speculation to judge the required i...

Claims

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Application Information

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IPC IPC(8): G06T7/33
CPCG06T7/337G06T2207/10081G06T2207/10088G06T2207/10132
Inventor 郭树理韩丽娜郝晓亭陈启明司全金林辉刘宏斌刘宏伟陈迁刘思雨王娟郭芙苏
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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